Category: market risk

I reader asked why so many practitioners use high Equity Risk Premiums in their valuations and fairness opinions.

In particular, he mentioned a specific assumption set he had seen including:

ERP of 6.8%

company specific risk premium of 4%

He also commented on how haphazard the use of risk premiums can be and referenced a few sources I’ve used myself.

The ERP of 6.8% does seem high. However, it really isn’t possible to comment on the specifics of the company specific risk premium without knowing the company.

Although I haven’t updated my research on this in a few years, in my own work I still generally stick with a range of 3% to 5% for an ERP, before considering company specific factors, liquidity, and so on. Historically / empirically estimated ERPs shouldn’t change frequently since the time series used is long. Another few years on a 20 year estimation period shouldn’t have much impact.

A recent article in The Actuary magazine addressed whether “de-risking in members’ best interests?” I say “recent” even though it’s from August because I am a little behind on my The Actuary reading.

In the article, the authors demonstrate that by modelling the impact of covenant risk, optimal investment portfolios for Defined Benefit (DB) pensions actually have more risky assets than if this covenant risk is ignored.

The covenant they refer to is the obligation of the sponsor to make good deficits within the pension fund. Covenant risk then is the risk that the sponsor is unable (typically through its own insolvency) to make good on this promise.

On the surface it should seem counterintuitive that by modelling an additional risk to pensioners, the answer is to invest in riskier assets, thus increasing risk.

The explanation proffered by the authors is that the higher expected returns from riskier assets allow the fund to potentially build up surplus, thus reducing the risks of covenant failure.

Aviva in France is still dealing with having written the worst insurance policy in the world. From the sounds of things, they weren’t alone in this foible. It’s also hard to say as an outsider what the right or reasonable resolution to their current problem is, but here is the policy that they wrote.

Buy a policy

Choose what funds you want to invest in

Unit prices calculated each Friday

Allow policyholders to switch funds on old prices until the next week

Hope like hell policyholders don’t switch out of poorly performing funds into well performing funds with perfect information based on backwards, stale prices.

Inconceivable – and since I don’t know more than I read on this blog post, maybe the reality and liability is really quite different.

South Africa has a pretty rich history of banking failures. This paper, part of a masters, by Sipho Makhubela, provides an interesting over of banking failures since 1994. I haven’t read the entire paper yet, but Section 4 (starting on page 72) outlines the background behind banking failures in South Africa and is fascinating reading in its own right.

It’s worth reading in its entirety for the insights. I don’t agree with everything there, and I certainly don’t agree with the widely held view (not among the authors) that the universe of countries included in the survey is supposed to be somehow representative of the world.

The countries chosen have an absolutely clear bias in their selection. They are successful economies with successful financial markets. They are included by virtue of their long-term success and capital growth and returns for investors.

The authors know this, but many readers don’t. The returns per this survey are an overly rosy view of possible future returns.

As part of the run-up to my overview of my own predictions for 2012, I thought i should highlight why I bother at all.
Most predictions, most of the time, will be wrong. Crystal balls aside, it is nearly impossible to reliably, accurately predict future complex events. However, the process of rigorously considering what might happen, what could go wrong, what the drivers of change are – all of those are really useful.
But why then bother making ultimate predictions if the “process” is where the value is? As it turns out, making the final prediction is part of the process. Paying poker without money at stake is a pointless exercise; there are no consequences to poor play (be it luck or skill that was lacking).
Making that firm and final prediction is important to ensure the process was rigorous and not an off the cuff guess.
Finally, evaluating part performance can’t suggest whether the predictions are improving, whether they are consistently biased or whether the system is working.
So, most predictions are wrong, but some are useful.

The Technical Provisions Task Group and KPMG ran a workshop for industry participation on risk-free rates recently. The idea was to see whether we could improve the extent and quality of industry comment on key, controversial areas of the proposed SAM regime.

Turnout was good, but not great, but the discussion and points raised were all fantastic. Plenty more to do from here onwards, but I thought it might be useful to include the presentations somewhere publicly available.

Some of the concepts that were on the agenda

Swaps vs Bonds, the theory as well as practical implications for insurers, banks and the capital markets

Extrapolation methods and what challenges this creates for practitioners